AIMC Topic: Reproducibility of Results

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Multi-Disease Detection in Retinal Imaging Based on Ensembling Heterogeneous Deep Learning Models.

Studies in health technology and informatics Sep 21, 2021
Preventable or undiagnosed visual impairment and blindness affect billion of people worldwide. Automated multi-disease detection models offer great potential to address this problem via clinical decision support in diagnosis. In this work, we propose...
Deep Learning Humans Diagnostic Imaging Neural Networks, Computer Retina Reproducibility of Results
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Improving feature selection performance for classification of gene expression data using Harris Hawks optimizer with variable neighborhood learning.

Briefings in bioinformatics Sep 2, 2021
Gene expression profiling has played a significant role in the identification and classification of tumor molecules. In gene expression data, only a few feature genes are closely related to tumors. It is a challenging task to select highly discrimina...
Cluster Analysis Machine Learning Humans Algorithms Mutation Databases, Factual Reproducibility of Results Internet Computational Biology Animals Gene Expression Regulation, Neoplastic Neoplasms Models, Genetic Gene Expression Profiling
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usDSM: a novel method for deleterious synonymous mutation prediction using undersampling scheme.

Briefings in bioinformatics Sep 2, 2021
Although synonymous mutations do not alter the encoded amino acids, they may impact protein function by interfering with the regulation of RNA splicing or altering transcript splicing. New progress on next-generation sequencing technologies has put t...
Humans Computational Biology Machine Learning Models, Genetic Algorithms Proteins Reproducibility of Results Silent Mutation
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Integrating multi-scale neighbouring topologies and cross-modal similarities for drug-protein interaction prediction.

Briefings in bioinformatics Sep 2, 2021
MOTIVATION: Identifying the proteins that interact with drugs can reduce the cost and time of drug development. Existing computerized methods focus on integrating drug-related and protein-related data from multiple sources to predict candidate drug-t...
Drug Development Support Vector Machine Proteins Pharmaceutical Preparations Reproducibility of Results Protein Binding Computational Biology Models, Theoretical Humans Machine Learning Algorithms
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SAResNet: self-attention residual network for predicting DNA-protein binding.

Briefings in bioinformatics Sep 2, 2021
Knowledge of the specificity of DNA-protein binding is crucial for understanding the mechanisms of gene expression, regulation and gene therapy. In recent years, deep-learning-based methods for predicting DNA-protein binding from sequence data have a...
Humans Neural Networks, Computer Binding Sites Algorithms Computational Biology Reproducibility of Results DNA Deep Learning Internet Protein Binding DNA-Binding Proteins
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A comprehensive review of the imbalance classification of protein post-translational modifications.

Briefings in bioinformatics Sep 2, 2021
Post-translational modifications (PTMs) play significant roles in regulating protein structure, activity and function, and they are closely involved in various pathologies. Therefore, the identification of associated PTMs is the foundation of in-dept...
Models, Biological Protein Processing, Post-Translational Proteins Databases, Protein Humans Neural Networks, Computer Machine Learning Algorithms Reproducibility of Results Computational Biology
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DeepDTAF: a deep learning method to predict protein-ligand binding affinity.

Briefings in bioinformatics Sep 2, 2021
Biomolecular recognition between ligand and protein plays an essential role in drug discovery and development. However, it is extremely time and resource consuming to determine the protein-ligand binding affinity by experiments. At present, many comp...
Hydrogen Bonding Binding Sites Protein Conformation, alpha-Helical Deep Learning Protein Binding Proteins Models, Molecular Amino Acid Sequence Ligands Data Accuracy Software Reproducibility of Results Drug Discovery
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Deep embedded clustering with multiple objectives on scRNA-seq data.

Briefings in bioinformatics Sep 2, 2021
In recent years, single-cell RNA sequencing (scRNA-seq) technologies have been widely adopted to interrogate gene expression of individual cells; it brings opportunities to understand the underlying processes in a high-throughput manner. Deep embedde...
Humans Neural Networks, Computer Algorithms Reproducibility of Results Computational Biology Models, Genetic Cluster Analysis Mutation Gene Expression Profiling Single-Cell Analysis RNA-Seq Gene Ontology
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Identification of active molecules against Mycobacterium tuberculosis through machine learning.

Briefings in bioinformatics Sep 2, 2021
Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb) and it has been one of the top 10 causes of death globally. Drug-resistant tuberculosis (XDR-TB), extensively resistant to the commonly used first-line drugs, has e...
Area Under Curve Antitubercular Agents Tuberculosis, Multidrug-Resistant Models, Biological Mycobacterium tuberculosis Data Accuracy Reproducibility of Results Humans Drug Discovery Neural Networks, Computer ROC Curve Support Vector Machine
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A spatial-temporal gated attention module for molecular property prediction based on molecular geometry.

Briefings in bioinformatics Sep 2, 2021
MOTIVATION: Geometry-based properties and characteristics of drug molecules play an important role in drug development for virtual screening in computational chemistry. The 3D characteristics of molecules largely determine the properties of the drug ...
Reproducibility of Results Drug Discovery Deep Learning Protein Binding Neural Networks, Computer Software Algorithms Molecular Structure Pharmaceutical Preparations Ligands Molecular Conformation Computational Biology Proteins Models, Molecular Humans
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